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Converging data that attribute a central role to sleep in memory consolidation have increased the interest to understand the characteristics of the hippocampal sleep and their relations with the processing of new information. Neural synchronization between different brain regions is thought to be implicated in long-term memory consolidation by facilitating neural communication and by promoting neural plasticity. However, the majority of studies have focused their interest on intra-hippocampal, rhinal-hippocampal or cortico-hippocampal synchronization, while inter-hemispheric synchronization has been so far neglected. To clarify the features of spontaneous human hippocampal activity and to investigate inter-hemispheric hippocampal synchronization across vigilance states, pre-sleep wakefulness and nighttime sleep were recorded from right and left homologous hippocampal loci using stereo-EEG techniques. Hence, quantitative and inter-hemispheric coherence analyses of hippocampal activity across sleep and waking states were carried out. The results showed the presence of delta activity in human hippocampal spontaneous EEG also during wakefulness. The activity in the delta range exhibited a peculiar bimodal distribution, namely a low frequency non-oscillatory activity (up to 2Hz) synchronized between hemispheres mainly during wake and REM sleep, and a faster oscillatory rhythm (2-4Hz). The latter was less synchronized between the hippocampi and seemed reminiscent of animal RSA (rhythmic slow activity). Notably, the low-delta activity showed high inter-hemispheric hippocampal coherence during REM sleep and, to a lesser extent, during wakefulness, paralleled by a (unexpected) decrease of coherence during NREM sleep. Therefore, low-delta hippocampal state-dependent synchronization starkly contrasts with neocortical behavior in the same frequency range. Further studies might shed light on the role of these low frequency rhythms in the encoding processes during wakefulness and in the consolidation processes during subsequent sleep.

Sleep is traditionally considered a global process involving the whole brain. However, recent studies have shown that sleep depth is not evenly distributed within the brain. Sleep disorders, such as sleepwalking, also suggest that EEG features of sleep and wakefulness might be simultaneously present in different cerebral regions. In order to probe the coexistence of dissociated (wake-like and sleep-like) electrophysiological behaviors within the sleeping brain, we analyzed intracerebral electroencephalographic activity drawn from sleep recordings of five patients with pharmacoresistant focal epilepsy without sleep disturbances, who underwent pre-surgical intracerebral electroencephalographic investigation. We applied spectral and wavelet transform analysis techniques to electroencephalographic data recorded from scalp and intracerebral electrodes localized within the Motor cortex (Mc) and the dorso-lateral Prefrontal cortex (dlPFc). The Mc showed frequent Local Activations (lasting from 5 to more than 60s) characterized by an abrupt interruption of the sleep electroencephalographic slow waves pattern and by the appearance of a wake-like electroencephalographic high frequency pattern (alpha and/or beta rhythm). Local activations in the Mc were paralleled by a deepening of sleep in other regions, as expressed by the concomitant increase of slow waves in the dlPFc and scalp electroencephalographic recordings. These results suggest that human sleep can be characterized by the coexistence of wake-like and sleep-like electroencephalographic patterns in different cortical areas, supporting the hypothesis that unusual phenomena, such as NREM parasomnias, could result from an imbalance of these two states.

Recent evidence suggests that slow EEG rhythms are involved in post-learning plasticity. However, the relationships between memory consolidation and hippocampal EEG features remain unclear. Here, we assessed the effects of both procedural and declarative learning on qualitative and quantitative measures of sleep by recording stereo-EEG (SEEG) directly from the hippocampus and the neocortex in a group of epileptic patients undergoing pre-surgical evaluations. Following a baseline night, sleep was recorded after administration of a declarative (paired-associate word list learning task) and a procedural (sequential finger tapping) task. Patients were tested before going to bed (test) and after sleep in the following morning (retest). At retest, we found that patients recalled correctly more word pairs compared to the pre-sleep test (declarative task), and they were slightly faster in performing the motor task (procedural task). Standard polysomnography showed an increase in the amount of slow-wave sleep (SWS) only after procedural learning, paralleled by an increase of hippocampal SEEG power in the very low frequency range (VLF, 0.5-1 Hz) during the first NREM sleep cycle. Moreover, procedural performance enhancement and SEEG power increase in the hippocampal VLF were significantly correlated, indicating a link between procedural memory consolidation and slow hippocampal SEEG rhythms. These findings are consistent with the hypothesis of synaptic homeostasis occurring during sleep, suggesting that hippocampal slow oscillations are associated with local processes of post-learning synaptic downscaling

BACKGROUND: There is compelling evidence indicating that sleep plays a crucial role in the consolidation of new declarative, hippocampus-dependent memories. Given the increasing interest in the spatiotemporal relationships between cortical and hippocampal activity during sleep, this study aimed to shed more light on the basic features of human sleep in the hippocampus. METHODOLOGY/PRINCIPAL FINDINGS: We recorded intracerebral stereo-EEG directly from the hippocampus and neocortical sites in five epileptic patients undergoing presurgical evaluations. The time course of classical EEG frequency bands during the first three NREM-REM sleep cycles of the night was evaluated. We found that delta power shows, also in the hippocampus, the progressive decrease across sleep cycles, indicating that a form of homeostatic regulation of delta activity is present also in this subcortical structure. Hippocampal sleep was also characterized by: i) a lower relative power in the slow oscillation range during NREM sleep compared to the scalp EEG; ii) a flattening of the time course of the very low frequencies (up to 1 Hz) across sleep cycles, with relatively high levels of power even during REM sleep; iii) a decrease of power in the beta band during REM sleep, at odds with the typical increase of power in the cortical recordings. CONCLUSIONS/SIGNIFICANCE: Our data imply that cortical slow oscillation is attenuated in the hippocampal structures during NREM sleep. The most peculiar feature of hippocampal sleep is the increased synchronization of the EEG rhythms during REM periods. This state of resonance may have a supportive role for the processing/consolidation of memory.

STUDY OBJECTIVE: We present a mathematical model of sleep-EEG structure applied to the analysis of sleep patterns in narcoleptics by combining the 2-process model of sleep regulation and the reciprocal interaction model of REM regulation suggested by McCarley and Hobson. The aim was the individuation of parameters characterizing narcoleptic sleep in comparison to controls. DESIGN: Polysomnographic data were drawn from a previous study about sleep in narcolepsy. The mathematical model was fitted to quantitative EEG data by an optimization procedure. SETTING: Polysomnographic data were recorded in single and sound attenuated hospital rooms, for one night following an adaptation night. PARTICIPANTS: 9 narcoleptic subjects (7 males, 2 females, mean age 39.6 +/- 4.3 years) and 9 age- and sex- matched controls. MEASUREMENTS: Slow Wave Activity (SWA) time series were evaluated by spectral analysis. The sleep model was fitted to SWA profile for each recording and to the averaged SWA profile for each group. Bartlett and Kolmogorov-Smirnov test were used to evaluate the goodness of fit and the accuracy of model predictions. RESULTS: In both controls and narcoleptics the optimization procedure produced a good fit of SWA raw data. The only significant difference between the groups were the RemOn/RemOff coupling parameters, reflecting an enhanced strength of the REM oscillator in narcoleptics. CONCLUSIONS: The mathematical model of sleep provides a substantial description of empirical patterns for both controls and narcoleptics. The variation of values in the parameters describing the strength of RemOn /RemOff interaction is the major feature characterizing narcoleptics; it can explain sleep onset REM periods (SOREMPs) and variations of REM-NREM sleep cycle duration.

There is growing evidence that cyclic alternating pattern (CAP) and arousals are woven into the basic mechanisms of sleep regulation. In the present study, the overnight sleep cycles (SC) of 20 normal subjects were analyzed according to their stage composition, CAP rate, phase A subtypes and arousals. Individual SC were then divided into 10 normalized temporal epochs. CAP parameters and arousals were measured in each epoch and averaged in relation to the SC order. Subtypes A2 and A3 of CAP in non-rapid eye movement (NREM) sleep, and arousals, both in REM and NREM sleep when not coincident with a A2 or A3 phases, were lumped together as fast electroencephalographic (EEG) activities (FA). Subtypes A1 of CAP, characterized by slow EEG activities (SA), were analyzed separately. The time distribution of SA and FA was compared to the mathematical model of normal sleep structure including functions representing the homeostatic process S, the circadian process C, the ultradian process generating NREM/REM cycles and the slow wave activity (SWA) resulting from the interaction between homeostatic and ultradian processes. The relationship between SA and FA and the sleep-model components was evaluated by multiple regression analysis in which SA and FA were considered as dependent variables while the covariates were the process S, process C, SWA, REM-on and REM-off activities and their squared values. Regression was highly significant (P < 0.0001) for both SA and FA. SA were prevalent in the first three SC, and exhibited single or multiple peaks immediately before and in the final part of deep sleep (stages 3 + 4). The peaks of FA were delayed and prevailed during the pre-REM periods of light sleep (stages 1 + 2) and during REM sleep. SA showed an exponential decline across the successive SC, according to the homeostatic process. In contrast, the distribution of FA was not influenced by the order of SC, with periodic peaks of FA occurring before the onset of REM sleep, in accordance with the REM-on switch. The dynamics of CAP and arousals during sleep can be viewed as an intermediate level between cellular activities and macroscale EEG phenomena as they reflect the decay of the homeostatic process and the interaction between REM-off and REM-on mechanisms while are slightly influenced by circadian rhythm.

Shift-work disrupts the sleep-wake cycle and could bring about sleep disorders and excessive daytime sleepiness. We studied two samples of shift-workers, a group of 178 nurses and one of 174 police officers, all working in the town of Palermo (Italy); their answers to a sleep disorder questionnaire were scored and added in order to create a Sleep Disorder Score (SDS). The SDS cut-off value, discrimining pathological values from physiological ones, was settled a-priori. In both groups SDS did not depend on sex, age, weight, height nor on working seniority, but it increased non linearly (cubic form) with shift-work seniority. In nurses this mathematical description of SDS exceeded the cut-off value after 15 years of shift-work seniority; in police officers it settled asymptotically under the critical value. This could be ascribable both to the different composition in sex of the two samples (nurses: 49% F-51% M vs. police officers: 6% F-94% M) both to the self-selection process that seems to undergo police officers (nurses do not leave shift-work because of salary incentives).

STUDY OBJECTIVES: Night work can be dangerous because both circadian sleep propensity (process C) and sleep pressure due to the prolonged wakefulness (process S) contribute to the reduction of vigilance levels. As naps are a countermeasure to sleepiness, this study evaluates the role they play in preventing sleep-related accidents in Italian shift-working police drivers. DESIGN/SETTING/PARTICIPANTS: The study concerns highway car accidents that occurred to Italian shift-working police drivers; it was performed in 2 steps: a retrospective analysis of the overall number of accidents that occurred during the years 1993--1997 (n, 1195), followed by a validation analysis of a smaller cohort of accidents prospectively collected during 2003 (n, 84). INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: RETROSPECTIVE ANALYSIS: The influence of process S, process C, driver characteristics, and context conditions on accident risk, estimated by means of Cox hazard regression, revealed that nighttime accident risk was mainly influenced by process S levels. Consequently, an experimental mathematical model linking the hourly observed number of accidents to process S levels was designed. Its generalization to the theoretical case of drivers omitting naps showed an increase of about 38% of accidents. PROSPECTIVE ANALYSIS: In order to validate our results, we compared retrospective and prospective sleep patterns: no statistical difference was found. Again, the hourly number of accidents increased with homeostatic sleep pressure; the theoretical efficacy of napping was quantified in 48% accidents decrease. CONCLUSIONS: Our data seem to confirm that napping before working a night shift is an effective countermeasure to alertness and performance deterioration associated with night work. Moreover, this self-initiated behavior could have a prophylactic efficacy in reducing the number of car accidents.

A number of phasic events influence sleep quality and sleep macrostructure. The detection of arousals and the analysis of cyclic alternating patterns (CAP) support the evaluation of sleep fragmentation and instability. Sixteen polygraphic overnight recordings were visually inspected for conventional Rechtscaffen and Kales scoring, while arousals were detected following the criteria of the American Sleep Disorders Association (ASDA). Three electroencephalograph (EEG) segments were associated to each event, corresponding to background activity, pre-arousal period and arousal. The study was supplemented by the analysis of time-frequency distribution of EEG within each subtype of phase A in the CAP. The arousals were characterized by the increase of alpha and beta power with regard to background. Within NREM sleep most of the arousals were preceded by a transient increase of delta power. The time-frequency evolution of the phase A of the CAP sequence showed a strong prevalence of delta activity during the whole A1, but high amplitude delta waves were found also in the first 2/3 s of A2 and A3, followed by desynchronization. Our results underline the strict relationship between the ASDA arousals, and the subtype A2 and A3 within the CAP: in both the association between a short sequence of transient slow waves and the successive increase of frequency and decrease of amplitude characterizes the arousal response.

BACKGROUND AND PURPOSE: Periodic limb movement disorder (PLMD) is frequently accompanied by awakenings or signs of EEG arousal. However, it is matter of debate whether EEG arousals trigger leg movements or both EEG arousal and leg movements are separate expressions of a common pathophysiological mechanism. Previous studies showed that cardiac and cerebral changes occur in association with periodic limb movements (PLMs), and that a combining increase in delta activity and in heart rate (HR) occurs before the onset of PLMs. PATIENTS AND METHODS: This paper presents some preliminary data, obtained from a sample of 5 subjects with PLMD not associated to restless legs syndrome. To describe the temporal pattern of cardiac and EEG activities changes concomitant with PLMs in NREM sleep we used time frequency analysis technique. RESULTS: PLM onset is heralded by a significant activation of HR and delta activity power, beginning 4.25 and 3 s respectively before PLMs onset, with PLMs onset and arousal onset falling together. DISCUSSION: Delta and HR variations herald PLMs and activation of fast EEG frequencies. Such a stereotyped pattern is common in PLMs and in spontaneous or stimuli-induced arousals. Moreover a similar pattern seems to encompass the CAP phenomenon. The whole of these phenomena can be linked to the activity of a common brainstem system, which receives peripheral inputs, regulating the vascular, cardiac and respiratory activities and synchronizing them to cortical oscillations of EEG.

Background and purpose To carry out an observational epidemiological survey (Studio Morfeo), to determine: (1) the frequency of insomnia in a large Italian population presenting directly to the general physician (GP); (2) the impact of insomnia on the quality of life, on the use of health-care resources and on co-morbidity. Patients and methods The study was accomplished by GPs, trained by sleep specialists accredited by the Italian Association of Sleep Medicine. Only patients spontaneously presenting to their GP for medical problems were surveyed. Each GP was asked to enroll at least five patients across a routine week of medical activity including both morning and afternoon clinics. The first patient of each weekday was recruited after obtaining written consent. According to the responses to the sleep-related questions, patients were classified into three categories: (1) no insomnia, (2) level 1 insomnia with absence of day-time dysfunction and (3) level 2 insomnia with presence of day-time dysfunction. Results A total of 3284 patients were enrolled by 738 GPs in this Italian survey. Insomnia was reported by 64% of all interviewed patients, with 20% classified as level 1 and 44% as level 2. Logistic analysis indicated that depression (odds ratio, 2.70), involvement of >1 organ systems (odds ratio, 1.24), female gender (odds ratio, 1.19), unemployment (odds ratio, 1.18), low education (odds ratio, 1.18) and increasing age (odds ratio, 1.02) were the major risk factors for insomnia. Conclusions Our findings indicate that insomnia is a frequent disturbance in the Italian primary care population, is associated with high risk of co-morbid conditions, and results in increased use of health-care resources.